Reducing user fatigue within an interactive evolutionary design system using clustering and case-based reasoning

Abstract

User fatigue is a limiting factor in interactive evolutionary design and optimization systems. This work illustrates how user fatigue arising from repetitive evaluations can be reduced by incorporating a case-based machine learning system and by clustering the population. An interactive evolutionary design system for urban furniture design is introduced and used as a test-bed for the implementation. The role of clustering within the system is described and initial results are presented. Results obtained from previous work supporting the choice of a case-based approach to machine learning are then presented and, finally, the results from a multi-user study of the performance of the case-based learning system when applied to the design of urban furniture are included.

Keywords:

• Machine learning
• evolutionary algorithms
• conceptual design
• software agents